January 9, 2020
For Special Track PPODS Protecting Privacy in Open (& big) Data Settings (PPODS) New submission deadline: February 05, 2020 Along with ICDS 2020 The Fourteenth International Conference on Digital Society (ICDS)
March 22 – 26, 2020
Open Data and Privacy
Public organizations, as well as private enterprises, collect data directly as the input necessary for provisioning their services (like contact information of individuals and citizens) or indirectly as the byproduct of their service provisioning (like the process information related to the chain of actions and interventions). Governments want to proactively share their data sets with the public. Via this socalled Open Data approach, governments intend to improve their transparency, accountability and efficiency, to support participatory governance by citizens, to foster innovations and economic growth, and to empower citizens and businesses for making informed decisions. In order to achieve these objectives, public organizations strive to open their data sets as raw as possible. But the collected data often pertain to natural persons (e.g., citizens, clients, employees or partners) and therefore contain privacy sensitive personal information.
Opening such data as raw as possible is, therefore, subject to privacy risks (i.e., personal data disclosure risks) with adverse impacts on the fundamental human rights of individuals as well as on their dignity, liberty, autonomy and income. Linking the opened data sets to other data sets can also reveal more privacysensitive information about individuals than that in those opened data sets. Consequently, protecting the privacy of citizens and individuals is an important precondition for public organizations for opening their data sets.
Big Data and Privacy
Further, we currently witness the rise of the Big Data paradigm as there are a huge amount of data being generated, collected, analyzed and distributed at a fast pace. This growth is due to the proliferation of many connected devices (such as cameras, smart phones, sensors, and smart household appliances), widespread and intensive usage of social networks, and digital transformation of business and organizational processes and services. There is a growing demand to make use of Big Data and develop (new) applications and services that ease our daily lives, create added values for businesses, provide insight in societal phenomena, and guide policymaking processes. Often Big Data usage does not fully coincide with the purpose for which the data were originally collected. Using the Big Data gathered from various sources and for diverse purposes, for example, can violate privacy rights of individuals and result in personal data disclosures. On the one hand, the data growth makes it difficult to detect and deal with those data disclosure risks that are hidden in the data set (i.e., the intrinsic risk factors). On the other hand, the growth of other data sets (i.e., the increase of the socalled background knowledge available to other parties) makes it difficult to assess and deal with the data disclosure risks that may arise when combining own data sets with the other data sets (i.e., the extrinsic risk factors). Consequently, Big Data makes it difficult for data controllers to share their data with specific groups, individuals or the public in a responsible way.
Topics and Scope
The aim of this special track is to foster research on the methodologies, concepts, policies, procedures and technologies that contribute to protecting personal information in Open Data and/or Big Data settings, while preserving their utility for addressing societal issues and creating added business values. We invite researchers and practitioners from academia, industries and public organizations to present their innovative (applied) research results or novel approaches and methods related, but not limited, to the following topics.
Applications areas of Big & Open Data in a responsible way like:
Data protection technologies, procedures and policies in Big & Open Data settings like:
Other relevant topics like:
data quality issues,
misinterpretation and misunderstanding aspects, and
ethical issues (e.g., discrimination).
Note that the submitted work should be related to the general topics of the track in some way. In case of any doubt, please feel free to contact the track chairs.
Inform the chairs as soon as you decide to contribute.
Note: The submission deadline is somewhat flexible, providing that the arrangements are made ahead of time with the chairs.
Before submission, please check and comply with the editorial rules: http://www.iaria.org/editorialrules.html
Please see https://www.iariasubmit.org/conferences/submit/newcontribution.php?event=ICDS+2020+Special
(select Track Preference as PPODS).
Each accepted paper needs at least one full registration, before the cameraready manuscript can be included in the proceedings.
Registration fees are available at http://www.iaria.org/registration.html